• Lead complex end-to-end deployments in production at strategic customers.
• Lead the discovery, design, development, and deployment of high-impact AI / GenAI-powered solutions in close collaboration with client stakeholders.
• Build LLM-driven applications, RAG systems, and agentic workflows that demonstrate measurable business value.
• Drive innovation by creating reusable accelerators, frameworks, and reference implementations for enterprise GenAI deployments.
• Enable rapid experimentation and large-scale adoption of AI, data, and cloud platforms through hands-on engineering leadership.

Key Responsibilities

• Partner with client business and engineering teams to translate complex problems into executable GenAI solutions.
• Own solution delivery end‑to‑end, from discovery and architecture through production deployment.
• Act as a trusted technical advisor to senior and executive client stakeholders.
• Design and build LLM‑powered applications, including copilots, assistants, RAG systems, and agentic workflows.
• Integrate GenAI solutions with enterprise data platforms, APIs, and external systems.
• Optimize solutions across latency, cost, accuracy, scalability, security, and compliance.
• Convert PoCs into production‑grade, enterprise‑ready platforms through rapid iteration and feedback.
• Architect scalable, reliable, and observable systems using cloud‑native patterns.
• Develop reusable accelerators, reference architectures, and best practices for enterprise GenAI adoption.

Required Skills & Experience

Mandatory

• 3-5 years of experience in software engineering, data engineering, or AI/ML.
• Strong hands-on experience building, deploying, and operating production-grade systems.
• Expert-level proficiency in Python for large-scale, high-performance applications.
• Proven delivery experience in client-facing and high-ambiguity environments.
• Solid foundation in distributed systems, microservices, APIs, and cloud‑native architectures.
• Demonstrated ability to independently own and deliver complex, high-impact initiatives.
  • Excellent communicator, effective with both technical teams and business stakeholders and should have worked directly with clients.